Secure decision support system for healthcare professionals

Medical Secure Systems (MSSs) are represented by integrating calculation as well as physical processes. The speculations and utilizations of MSSs face the large problems. The main objective of this work is to provide a greater understanding of this emerging multidisciplinary methods. In this work system focusing on the MSS in medical applications, which is called as Medical Secure Systems (MSS). In MSS, different types on data can transfer to the private or public cloud for storage and processing. Over this information, machine learning algorithms can be combined to process that data, which will be further helpful to take a few decisions for healthcare expert. This information can be sensitive and is publically accessible and gave to outsider storage space, so that the difficult problem of security is emerges. To providing the security, in this paper we applied cryptographic method, for example, AES to encrypt the data before store on cloud servers. After this, to enhance the further security, system will utilize the idea of digital envelope. In this concept, information encryption AES key is again determined by utilizing ECC encryption key. Again to reduce the key management overhead, framework makes utilization of Key Distribution center (KDC), which can generate and deal with the keys for all users. At the last experimental results presented that, this MSS framework is more secure than existing one and it is additionally reduces the key management overhead. Also system gets less time and memory for implementing the system.